Data centers housing significant numbers of interconnected computing systems have become commonplace, such as private data centers that are operated by and on behalf of a single organization, and public data centers that provide access to computing resources to customers under various business models. For example, some public data center operators provide network access, power, and secure installation facilities for hardware owned by various customers, while other public data center operators provide “full service” facilities that also include the actual hardware resources used by their customers. However, as the scale and scope of typical data centers has increased, the task of provisioning, administering, and managing the physical computing resources has become increasingly complicated.
The advent of virtualization technologies for commodity hardware has provided a partial solution to the problem of managing large-scale computing resources for many customers with diverse needs. Generally described, virtualization technologies allow various computing resources to be efficiently and securely shared between multiple customers. For example, virtualization technologies, such as those provided by VMWare, XEN, or User-Mode Linux, may allow single physical computing machine resources to be shared among multiple users. More specifically, each user may be provided with one or more virtual machines hosted by the single physical computing machine, with each such virtual machine being a software simulation acting as a distinct logical computing system. Each virtual machine provides users with the experience that they are the sole operators and administrators of given hardware computing resources, while also providing application isolation and security among the various virtual machines. Furthermore, some virtualization technologies are capable of providing virtual resources that span one or more physical resources, such as a single virtual machine with multiple virtual processors that actually spans multiple distinct physical computing systems.
However, one problem that arises in the context of data centers that virtually or physically host large numbers of applications or systems for a set of diverse users involves managing the storage, distribution, and acquisition of copies of software applications. Applications may, for example, be quite large in size, making it costly (if not impossible) to have sufficient storage resources to store local copies of every hosted application on every computing system in the data center. However, it is also costly in terms of network bandwidth resources if a centralized storage location is alternatively maintained from which copies of applications are frequently transmitted to every computing system in the data center that is to execute those applications. In such an alternative, network bandwidth would be monopolized for the application copy transmittal and could prevent executing applications from receiving sufficient network bandwidth for their operation. Additionally, significant startup time latencies for application execution could be introduced while waiting for the application copy transmittals to be accomplished, etc. Such difficulties may be further exacerbated by various factors, such as the frequent introduction of new applications to be executed and/or the frequent deployment of successive versions of applications.
Thus, given such problems, it would be beneficial to provide techniques for distributing copies of applications in an efficient manner to computing systems that will execute the applications, as well to provide various other benefits.